The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'

Cognitive Science From the Perspective of Linguistic Diversity

This letter addresses two issues in language research that are important to cognitive science: the comparability of word meanings across languages and the neglect of an integrated approach to writing systems. The first issue challenges generativist claims by emphasizing the importance of comparability of data, drawing on typologists' findings about different languages. The second issue addresses the exclusion of diverse writing systems from linguistic investigation and argues for a more extensive study of their effects on language and cognition. We argue for a refocusing of cognitive science research on linguistic diversity in all modalities to develop the most robust understanding of language and its role in human cognition more broadly.

Explainability of neural networks for child language: Agent-First strategy in comprehension of Korean active transitive construction

This study investigates how neural networks address the properties of children's linguistic knowledge, with a focus on the Agent-First strategy in comprehension of an active transitive construction in Korean. We develop various neural-network models and measure their classification performance on the test stimuli used in a behavioural experiment involving scrambling and omission of sentential components at varying degrees. Results show that, despite some compatibility of these models' performance with the children's response patterns, their performance does not fully approximate the children's utilisation of this strategy, demonstrating by-model and by-condition asymmetries. This study's findings suggest that neural networks can utilise information about formal co-occurrences to access the intended message to a certain degree, but the outcome of this process may be substantially different from how a child (as a developing processor) engages in comprehension. This implies some limits of neural networks on revealing the developmental trajectories of child language. RESEARCH HIGHLIGHTS: This study investigates how neural networks address properties of child language. We focus on the Agent-First strategy in comprehension of Korean active transitive. Results show by-model/condition asymmetries against children's response patterns. This implies some limits of neural networks on revealing properties of child language.

Children learn ergative case marking in Hindi using statistical preemption and clause-level semantics (intentionality): evidence from acceptability judgment and elicited production studies with children and adults

Background: A question that lies at the very heart of language acquisition research is how children learn semi-regular systems with exceptions (e.g., the English plural rule that yields cats, dogs, etc, with exceptions feet and men). We investigated this question for Hindi ergative ne marking; another semi-regular but exception-filled system. Generally, in the past tense, the subject of two-participant transitive verbs (e.g., Ram broke the cup) is marked with ne, but there are exceptions. How, then, do children learn when ne marking is required, when it is optional, and when it is ungrammatical? Methods: We conducted two studies using (a) acceptability judgment and (b) elicited production methods with children (aged 4-5, 5-6 and 9-10 years) and adults. Results: All age groups showed effects of statistical preemption: the greater the frequency with which a particular verb appears with versus without ne marking on the subject - relative to other verbs - the greater the extent to which participants (a) accepted and (b) produced ne over zero-marked subjects. Both children and adults also showed effects of clause-level semantics, showing greater acceptance of ne over zero-marked subjects for intentional than unintentional actions. Some evidence of semantic effects at the level of the verb was observed in the elicited production task for children and the judgment task for adults. Conclusions: participants mainly learn ergative marking on an input-based verb-by-verb basis (i.e., via statistical preemption; verb-level semantics), but are also sensitive to clause-level semantic considerations (i.e., the intentionality of the action). These findings add to a growing body of work which suggests that children learn semi-regular, exception-filled systems using both statistics and semantics.

Korean-speaking children's constructional knowledge about a transitive event: Corpus analysis and Bayesian modelling

We investigate Korean-speaking children's knowledge about clause-level constructions involving a transitive event - active transitive and suffixal passive - through corpus analysis and Bayesian modelling. The analysis of Korean caregiver input and children's production in CHILDES revealed that the rates of constructional patterns produced by the children mirrored those uttered by the caregivers to a considerable degree and that the caregivers' use of case-marking was skewed towards single form-function pairings (despite the multiple form-function associations that the markers manifest). Based on these characteristics, we modelled a Bayesian learner by employing construction-based input (without considering lexical information). This simulation revealed the dominance of several constructional patterns, occupying most of the input, and their inhibitory effects on the development of the other patterns. Our findings illuminate how children shape clause-level constructional knowledge in Korean, an understudied language for this topic, as a function of input properties and domain-general learning capacities, appealing to the usage-based constructionist approach.

Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K'iche'

How do language learners avoid the production of verb argument structure overgeneralization errors ( *The clown laughed the man c.f. The clown made the man laugh), while retaining the ability to apply such generalizations productively when appropriate? This question has long been seen as one that is both particularly central to acquisition research and particularly challenging. Focussing on causative overgeneralization errors of this type, a previous study reported a computational model that learns, on the basis of corpus data and human-derived verb-semantic-feature ratings, to predict adults' by-verb preferences for less- versus more-transparent causative forms (e.g., * The clown laughed the man vs The clown made the man laugh) across English, Hebrew, Hindi, Japanese and K'iche Mayan. Here, we tested the ability of this model (and an expanded version with multiple hidden layers) to explain binary grammaticality judgment data from children aged 4;0-5;0, and elicited-production data from children aged 4;0-5;0 and 5;6-6;6 ( N=48 per language). In general, the model successfully simulated both children's judgment and production data, with correlations of r=0.5-0.6 and r=0.75-0.85, respectively, and also generalized to unseen verbs. Importantly, learners of all five languages showed some evidence of making the types of overgeneralization errors - in both judgments and production - previously observed in naturalistic studies of English (e.g., *I'm dancing it). Together with previous findings, the present study demonstrates that a simple learning model can explain (a) adults' continuous judgment data, (b) children's binary judgment data and (c) children's production data (with no training of these datasets), and therefore constitutes a plausible mechanistic account of the acquisition of verbs' argument structure restrictions.

When the independence of syntactic representation meets the sentence processing of Mandarin: Evidence from syntactic priming

There is no consensus on whether syntactic representation is independent of semantic representation in Mandarin. In four experiments, we adopted the syntactic priming paradigm to investigate the independence of syntactic representation in Mandarin. Experiments 1 and 2 investigated the priming effects of double object construction (DO) and prepositional object construction (PO) with the ditransitive verb being repeated across the prime and target. Experiment 1 showed two-way priming effects of DO and PO. Experiment 2 showed that the syntactic priming effects persisted regardless of whether the semantic features (animacy of the Theme) matched across the prime and target or not. Furthermore, such effects persisted in Experiments 3 and 4 where the ditransitive verb across the prime and target was not repeated. Taken together, these findings provide evidence that syntactic/semantic independence is universal and favoured over the traditional Chinese grammar account, which claims that the syntactic representation of Mandarin is not independent of the semantic representation.

How children learn to communicate discriminatively

How do children learn to communicate, and what do they learn? Traditionally, most theories have taken an associative, compositional approach to these questions, supposing children acquire an inventory of form-meaning associations, and procedures for composing / decomposing them; into / from messages in production and comprehension. This paper presents an alternative account of human communication and its acquisition based on the systematic, discriminative approach embodied in psychological and computational models of learning, and formally described by communication theory. It describes how discriminative learning theory offers an alternative perspective on the way that systems of semantic cues are conditioned onto communicative codes, while information theory provides a very different view of the nature of the codes themselves. It shows how the distributional properties of languages satisfy the communicative requirements described in information theory, enabling language learners to align their expectations despite the vastly different levels of experience among language users, and to master communication systems far more abstract than linguistic intuitions traditionally assume. Topics reviewed include morphological development, the acquisition of verb argument structures, and the functions of linguistic systems that have proven to be stumbling blocks for compositional theories: grammatical gender and personal names.

Direct Versus Indirect Causation as a Semantic Linguistic Universal: Using a Computational Model of English, Hebrew, Hindi, Japanese, and K'iche' Mayan to Predict Grammaticality Judgments in Balinese

The aim of this study was to test the claim that languages universally employ morphosyntactic marking to differentiate events of more- versus less-direct causation, preferring to mark them with less- and more- overt marking, respectively (e.g., Somebody broke the window vs. Somebody MADE the window break; *Somebody cried the boy vs. Somebody MADE the boy cry). To this end, we investigated whether a recent computational model which learns to predict speakers' by-verb relative preference for the two causatives in English, Hebrew, Hindi, Japanese, and K'iche' Mayan is able to generalize to a sixth language on which it has never been trained: Balinese. Judgments of the relative acceptability of the less- and more-transparent causative forms of 60 verbs were collected from 48 native-speaking Balinese adults. The composite crosslinguistic computational model was able to predict these judgments, not only for verbs that it had seen, but also--in a split-half validation test--to verbs that it had never seen in any language. A "random-semantics" model showed only a relatively small decrement in performance with seen verbs, whose behavior can be learned on a verb-by-verb basis, but achieved zero correlation with human judgments when generalizing to unseen verbs. Together, these findings suggest that Balinese conceptualizes directness of causation in a similar way to these unrelated languages, and therefore constitute support for the view that the distinction between more- versus less-distinct causation constitutes a morphosyntactic universal.